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4c3f59b70e
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/51166 Currently scale and zero_point values are stored as constant values in the graph. This prevents these values from being updated in the graph and also does not enable saving these values to state_dict After this PR we store scale/zero_point values for quantized ops as buffers in the root module and createe get_attr nodes for them in the graph. We also use the FQN of the module where the quantized ops are present to name these attributes so that they can be uniquely identified and mapped to quantized ops. Test Plan: python test/test_quantization.py TestQuantizeFx.test_qparams_buffers Imported from OSS Reviewed By: jerryzh168 Differential Revision: D26092965 fbshipit-source-id: b549b2d3dccb45c5d38415ce95a09c26f5bd590b |
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| .. | ||
| serialized | ||
| __init__.py | ||
| test_backward_compatibility.py | ||
| test_bias_correction.py | ||
| test_equalize.py | ||
| test_fusion_passes.py | ||
| test_numeric_suite.py | ||
| test_numeric_suite_fx.py | ||
| test_qat_module.py | ||
| test_quantize.py | ||
| test_quantize_fx.py | ||
| test_quantize_jit.py | ||
| test_quantized_functional.py | ||
| test_quantized_module.py | ||
| test_quantized_op.py | ||
| test_quantized_tensor.py | ||
| test_workflow_module.py | ||